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Title: Segmentation and recognition of text written in 3D using Leap motion interface
Authors: Agarwal C.
Dogra D.P.
Saini R.
Pratim Roy, Partha
Published in: Proceedings of 3rd IAPR Asian Conference on Pattern Recognition, ACPR 2015
Abstract: In this paper, we present a word extraction and recognition methodology from online cursive handwritten text-lines recorded by Leap motion controller The online text, drawn by 3D gesture in air, is distinct from usual online pen-based strokes. The 3D gestures are recorded in air, hence they produce often non-uniform text style and jitter-effect while writing. Also, due to the constraint of writing in air, the pause of stroke-flow between words is missing. Instead all words and lines are connected by a continuous stroke. In this paper, we have used a simple but effective heuristic to segment words written in air. Here, we propose a segmentation methodology of continuous 3D strokes into text-lines and words. Separation of text lines is achieved by heuristically finding the large gap-information between end and start-positions of successive text lines. Word segmentation is characterized in our system as a two class problem. In the next phase, we have used Hidden Markov Model-based approach to recognize these segmented words. Our experimental validation with a large dataset consisting with 320 sentences reveals that the proposed heuristic based word segmentation algorithm performs with accuracy as high as 80.3%c and an accuracy of 77.6% has been recorded by HMM-based word recognition when these segmented words are fed to HMM. The results show that the framework is efficient even with cluttered gestures. © 2015 IEEE.
Citation: Proceedings of 3rd IAPR Asian Conference on Pattern Recognition, ACPR 2015, (2016), 539- 543
Issue Date: 2016
Publisher: Institute of Electrical and Electronics Engineers Inc.
Keywords: Computational linguistics
Hidden Markov models
Markov processes
Pattern recognition
Experimental validations
Handwritten texts
Jitter effect
Large dataset
Motion controller
Word recognition
Word segmentation
Character recognition
ISBN: 9.78148E+12
Author Scopus IDs: 57190285266
Author Affiliations: Agarwal, C., Department of CSE, NIT Rourkela, India
Dogra, D.P., School of Electrical Sciences, IIT Bhubaneswar, India
Saini, R., Department of CSE, IIT Roorkee, India
Roy, P.P., Department of CSE, IIT Roorkee, India
Appears in Collections:Conference Publications [CS]

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